Tomas Janssen
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View article: Primary endpoint analysis of the phase II DESTINATION-MRL trial for patients with intermediate-risk prostate cancer
Primary endpoint analysis of the phase II DESTINATION-MRL trial for patients with intermediate-risk prostate cancer Open
View article: Reliability of uncertainty quantification methods for deep learning auto-segmentation in head and neck organs at risk
Reliability of uncertainty quantification methods for deep learning auto-segmentation in head and neck organs at risk Open
Objective. Deep learning auto-segmentation has greatly advanced contouring in radiotherapy. However, quality assurance remains necessary due to performance fluctuation among individual patients. This manual process reintroduces variability…
View article: Impact of deep learning model uncertainty on manual corrections to MRI‐based auto‐segmentation in prostate cancer radiotherapy
Impact of deep learning model uncertainty on manual corrections to MRI‐based auto‐segmentation in prostate cancer radiotherapy Open
Background Deep learning (DL)‐based organ segmentation is increasingly used in radiotherapy. While methods exist to generate voxel‐wise uncertainty maps from DL‐based auto‐segmentation models, these maps are rarely presented to clinicians.…
View article: From standardized to individualized margins for online adaptive tumor dose escalation in rectal cancer
From standardized to individualized margins for online adaptive tumor dose escalation in rectal cancer Open
Our study demonstrated that distance to anorectal junction significantly influenced the magnitude and direction of the intrafraction motion of rectal cancer patients receiving SCRT, with distal tumors showing larger motion in the AP and CC…
View article: Weakly supervised commissioning of externally developed auto-segmentation models and applied to male pelvis MR auto-segmentation
Weakly supervised commissioning of externally developed auto-segmentation models and applied to male pelvis MR auto-segmentation Open
View article: Liver Metastases Treated With Magnetic Resonance Imaging Guided Stereotactic Body Radiation Therapy: Outcomes of Tolerability, Acute Toxicity, and Quality of Life From the MOMENTUM Study
Liver Metastases Treated With Magnetic Resonance Imaging Guided Stereotactic Body Radiation Therapy: Outcomes of Tolerability, Acute Toxicity, and Quality of Life From the MOMENTUM Study Open
View article: Dose adaptation to compensate for cumulative intra-fraction motion effects in online adaptive radiotherapy
Dose adaptation to compensate for cumulative intra-fraction motion effects in online adaptive radiotherapy Open
Objective. The objective of this work was to investigate the feasibility of using 0 mm PTV margin in online adaptive radiotherapy for the first fractions, in combination with treatment-specific local compensation of accumulated underdosage…
View article: Semi-Supervised Learning in Prostate MRI Tumor Segmentation Approaches Fully-Supervised Performance on External Validation
Semi-Supervised Learning in Prostate MRI Tumor Segmentation Approaches Fully-Supervised Performance on External Validation Open
Purpose To evaluate the diagnostic performance of semi-supervised learning models for aggressive prostate cancer segmentation on MRI compared to fully-supervised models trained with additional expert annotations. Materials and Methods We u…
View article: Leveraging network uncertainty to identify regions in rectal cancer clinical target volume auto-segmentations likely requiring manual edits
Leveraging network uncertainty to identify regions in rectal cancer clinical target volume auto-segmentations likely requiring manual edits Open
Our results validate the hypothesis that epistemic uncertainty estimates are a valuable tool to capture regions likely requiring clinically relevant edits.
View article: Multicentre prospective risk analysis of a fully automated radiotherapy workflow
Multicentre prospective risk analysis of a fully automated radiotherapy workflow Open
View article: Impact of deep learning model uncertainty on manual corrections to auto-segmentation in prostate cancer radiotherapy
Impact of deep learning model uncertainty on manual corrections to auto-segmentation in prostate cancer radiotherapy Open
Background: Deep learning (DL)-based organ segmentation is increasingly used in radiotherapy, yet voxel-wise DL uncertainty maps are rarely presented to clinicians. Purpose: This study assessed how DL-generated uncertainty maps impact radi…
View article: PTV Margins in MR-guided and Beam-gated SBRT of Liver Metastases: GTV Dose Escalation Can Reduce the Required PTV
PTV Margins in MR-guided and Beam-gated SBRT of Liver Metastases: GTV Dose Escalation Can Reduce the Required PTV Open
GTV dose escalation can reduce the required motion-related PTV margins in SBRT with motion management. The van Herk margin recipe overestimates PTV margins in SBRT with inhomogeneous target dose distributions and becomes less applicable wh…
View article: Simulation of Focal Boosting in Online Adaptive MRI-Guided SBRT for Patients With Locally Advanced Prostate Cancer With Seminal Vesicle Involvement
Simulation of Focal Boosting in Online Adaptive MRI-Guided SBRT for Patients With Locally Advanced Prostate Cancer With Seminal Vesicle Involvement Open
MRI-guidance can ensure high accuracy of focal boosting in patients with T3b disease. Because of the unfavorable location of the GTV, a lower boost dose was feasible compared to patients with T1-T3a PCa.
View article: Evaluation of deep learning-based target auto-segmentation for Magnetic Resonance Imaging-guided cervix brachytherapy
Evaluation of deep learning-based target auto-segmentation for Magnetic Resonance Imaging-guided cervix brachytherapy Open
Auto-segmentation introduces a bias in the manual delineations but this bias is clinically irrelevant. Auto-segmentation, particularly patient-specific fine-tuning, is a time-saving tool that can improve treatment logistics and therefore r…
View article: Geometrical and dosimetrical evaluation of different interpretations of a european consensus delineation guideline for the internal mammary lymph node chain in breast cancer patients
Geometrical and dosimetrical evaluation of different interpretations of a european consensus delineation guideline for the internal mammary lymph node chain in breast cancer patients Open
View article: Results of 2023 survey on the use of synthetic computed tomography for magnetic resonance Imaging-only radiotherapy: Current status and future steps
Results of 2023 survey on the use of synthetic computed tomography for magnetic resonance Imaging-only radiotherapy: Current status and future steps Open
View article: Quantifying and visualising uncertainty in deep learning-based segmentation for radiation therapy treatment planning: What do radiation oncologists and therapists want?
Quantifying and visualising uncertainty in deep learning-based segmentation for radiation therapy treatment planning: What do radiation oncologists and therapists want? Open
Preferences for uncertainty visualisation methods were assessed within a multi-institutional experienced group of clinicians. Further refinement of preferences may help in selecting the best options for clinical implementation.
View article: Incorporating patient-specific information for the development of rectal tumor auto-segmentation models for online adaptive magnetic resonance Image-guided radiotherapy
Incorporating patient-specific information for the development of rectal tumor auto-segmentation models for online adaptive magnetic resonance Image-guided radiotherapy Open
Patient-specific fine-tuning of automatically segmented rectal tumors, using images and segmentations from all previous fractions, yields superior quality compared to other auto-segmentation approaches.
View article: Evaluating the effect of higher Monte Carlo statistical uncertainties on accumulated doses after daily adaptive fractionated radiotherapy in prostate cancer
Evaluating the effect of higher Monte Carlo statistical uncertainties on accumulated doses after daily adaptive fractionated radiotherapy in prostate cancer Open
A 2-3 % MC statistical uncertainty was clinically feasible. Using a 2 % uncertainty setting reduced calculation times at the cost of limited relative dose-volume differences.
View article: Editorial: Magnetic resonance and artificial intelligence: online guidance for adaptive radiotherapy in abdominal and pelvic cancer treatment
Editorial: Magnetic resonance and artificial intelligence: online guidance for adaptive radiotherapy in abdominal and pelvic cancer treatment Open
Editorial: Magnetic resonance and artificial intelligence: online guidance for adaptive radiotherapy in abdominal and pelvic cancer treatment
View article: Interobserver variation in tumor delineation of liver metastases using Magnetic Resonance Imaging
Interobserver variation in tumor delineation of liver metastases using Magnetic Resonance Imaging Open
View article: Evaluation of Deep Learning Clinical Target Volumes Auto-Contouring for Magnetic Resonance Imaging-Guided Online Adaptive Treatment of Rectal Cancer
Evaluation of Deep Learning Clinical Target Volumes Auto-Contouring for Magnetic Resonance Imaging-Guided Online Adaptive Treatment of Rectal Cancer Open
Our framework provides a comprehensive evaluation of the performance and clinical usability of target auto-contouring models. Based on the results, we conclude that the model is eligible for clinical use.
View article: Evaluation of Deep Learning-Based Target Auto-Segmentation for Mri-Guided Cervix Brachytherapy
Evaluation of Deep Learning-Based Target Auto-Segmentation for Mri-Guided Cervix Brachytherapy Open
View article: Estro 2023 Survey on the Use of Synthetic Computed Tomography for Radiotherapy: Current Status and Future Steps
Estro 2023 Survey on the Use of Synthetic Computed Tomography for Radiotherapy: Current Status and Future Steps Open
View article: Clinical adoption of deep learning target auto-segmentation for radiation therapy: challenges, clinical risks, and mitigation strategies
Clinical adoption of deep learning target auto-segmentation for radiation therapy: challenges, clinical risks, and mitigation strategies Open
Radiation therapy is a localized cancer treatment that relies on precise delineation of the target to be treated and healthy tissues to guarantee optimal treatment effect. This step, known as contouring or segmentation, involves identifyin…
View article: Response letter to Wahid et al. regarding our publication “A network score-based metric to optimize the quality assurance of automatic radiotherapy target segmentations”
Response letter to Wahid et al. regarding our publication “A network score-based metric to optimize the quality assurance of automatic radiotherapy target segmentations” Open
View article: A network score-based metric to optimize the quality assurance of automatic radiotherapy target segmentations
A network score-based metric to optimize the quality assurance of automatic radiotherapy target segmentations Open
View article: Comparing adaptation strategies in MRI-guided online adaptive radiotherapy for prostate cancer: Implications for treatment margins
Comparing adaptation strategies in MRI-guided online adaptive radiotherapy for prostate cancer: Implications for treatment margins Open
ATP, ATR and ATS workflows ensure equal coverage of the CTVpros for the current clinical margins. For the CTVpros + sv, ATS showed optimal performance. GTV coverage improves by additional adaptations to prostate rotations.
View article: Health research with data and biosamples in a time of privacy: what information do patients want?
Health research with data and biosamples in a time of privacy: what information do patients want? Open
Health research with data and biosamples in a time of privacy: what information do patients want? 2 Background: Patients value transparency concerning the potential use of their clinical data and samples in research.However, it is usually …
View article: Health Research with Data in a Time of Privacy: Which Information do Patients Want?
Health Research with Data in a Time of Privacy: Which Information do Patients Want? Open
When hospitals ask broad consent for the secondary use of patient data for scientific research, it is unknown for which studies the data will be used. We investigated what patients at a cancer hospital consider to be an adequate level and …